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All Journal Journal of Applied Science, Engineering, Technology, and Education Variansi : Journal of Statistics and Its Application on Teaching and Research Quantitative Economics and Management Studies Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi ARRUS Journal of Engineering and Technology ARRUS Jurnal Pengabdian Kepada Masyarakat
Alfairus, Muh. Qodri
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Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Public Health Social Sciences Other

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Journal : ARRUS Journal of Engineering and Technology

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TSA App by R Shiny : Time Series Analysis Application for Univariate Series Data Tri Utomo, Agung; Ahmar, Ansari Saleh; Aidid, Muhammad Kasim; Rais, Zulkifli; Alfairus, Muh. Qodri
ARRUS Journal of Engineering and Technology Vol. 5 No. 1 (2025)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/jetech4398

Abstract

Time series analysis is a statistical method used to model and forecast sequential data over time. This modeling is typically performed using software, but most analytical tools require paid licenses. To address this issue, the TSA App by R Shiny is developed as an open-source application that is easily accessible. The application features a dashboard-based interface designed to help users perform univariate time series analysis without requiring programming skills. This study compares the analysis results of the TSA App with other software such as R Studio, Minitab, and Python. The results show that the TSA App produces comparable outputs in terms of visualization, ARIMA modeling, and forecasting accuracy. Therefore, the TSA App provides a practical and legal solution for time series analysis, especially for users who are unfamiliar with coding.
Co-Authors Abdul Rahman Ahmar, Ansari Saleh Aidid, Muhammad Kasim Akbar Iskandar Alsa, Yudhistira Ananda Karina Ayudhia Sasmito Mamadiyarov, Zokir Muhammad Arif Tiro Muhammad Kasim Aidid Pratama, Muh. Riyaldi Rahmat Hidayat Rais, Zulkifli Rajesh Kumar Ruliana Singagerda, Faurani Santi Sitti Masyitah Meliyana R. Sudarmin Tri Utomo, Agung Utriweni Mukhaiyar